I have installed the GTX 750 on my Linux box and it works. But it still uses 8.10. CPU usage is very high, near 100% on one of the 2 cores of the Opteron 1210, vintage 2008. The other is shared by Einstein, LHC@home and Atlas@home.
Tullio

Now I have an Atlas@home task running on two cores using VirtualBox and SETI@home using only 7% of CPU. Performance is not essential, I am running CERN projects using VirtualBox, Einstein@home and SETI@home using CPU. The Windows 10 PC, with GTX 1050 is using 8.19 with opencl_nvidia_SoG. That is my main SETI PC. I was wondering about the difference between OpenCL and CUDA on Linux.
Tullio

Hey, I have a large number of computers running the app, plus I worked on the original optimizations back in the Pentium !!! days. I'd like to help, though I'm out of touch with how far this has come in the past ten years so I may need some help configuring them the way you want them. I have the following nVidia cards in the PCs I am running:

In addition to these I have a bunch of computers doing the CPU/iGPU thing and several AMD low-end systems running as well. Here's my full list: https://setiathome.berkeley.edu/hosts_user.php?userid=3023
Anyhow, message me with instructions for how you want me to install and configure them and I'd be happy to help!

I have a GT 710 that does Seti GPU tasks on my Developer computer. I will be migrating from a Intel Duo (2 cpu) to an Intel i5 (4 core) shortly. I would prefer to continue to run Win7.

I am perfectly willing to setup the GPU for any kind of testing needed. It is running nicely, doing a standard Seti WU with no parameter files in about an hour and half, and then dropped to maybe a half hour when I put in the stock small card parms for the SOG command line.

I have two GT750 Ti cards I am running on my Xeon W3565. I am running a mixture that includes Seti Beta there. And it is picking up beta GPU runs. I am willing to tinker with these systems as long as I can get fairly specific instructions.

I am an amateur Web Developer with some exposure to software testing.

So to sum up. I would like to have at least one 750 gpu continue doing nothing but production. But I would be willing to devote the other one to "whatever" :)
If possible.

I sometimes don't see PM's immediately. If push comes to shove email me at tlgalenson at yahoo.com and include SETI in the subject line.

Tom"You are entitled to your own opinion but not to your own facts." Patrick Moynihan
"Without data, you are just another person with an opinion." Edward J. Demming

One of the compute nodes on my cluster has two Xeon E5-2670 10-core CPU's with hyperthreading, 128gb of memory and two Tesla K20Xm cards. I may be able to help with test builds (I'm running Centos 7) when the GPU's are idle.

Have no spare hardware or money but have testing skills and familiar with application tuning?
3. Run special test builds to help to adopt existing software to wide range of hardware devices of NVIDIA platform and help others to setup such builds for test.
Builds to be published in this thread or dedicated threads on Lunatics site (currently out of reach).

Have nothing but will to help?
4. Run special test builds on your own host and ask for help to install them on own host. There are enough peoples around who could help with initial setup.
Post links to build's processing results to help in testing.

I could do some test builds, but I'll need extra instructions for how to get started since I've never done builds for a BOINC project before.

Also, these builds can be done ONLY under Windows 10.

I have about 10 graphics board to get started with the testing, though. All Nvidia-based.

I could do some test builds, but I'll need extra instructions for how to get started since I've never done builds for a BOINC project before.

Also, these builds can be done ONLY under Windows 10.

I have about 10 graphics board to get started with the testing, though. All Nvidia-based.

What toolchain do you plan to use? VisualStudio? GCC? smth else?

I have PARTS of the Visual Studio, GCC, and Cygwin tool chains installed. I'm familiar enough with the Cygwin tool chain to tell that it is probably not suitable for GPU work. I'm not familiar enough with the others to tell what I'm missing. However, I'll probably install any toolchain that is free and appears to be from a reliable source. I'm likely to need help getting started with any toolchain other than Cygwin, though.

I've finished an online CUDA class that used a toolchain on the class's server, but did not say enough about how to install a usable toolchain on my own computer and start using it. I no longer have access to the class's server.

Then you have to learn some environment to work with first perhaps.
All Windows GPU builds were done with VS AFAIK.
All OpenCL ones - definitely.
So easiest way is to install VisualStudio environment and use VC++ toolchain.
For GPU build you'll need SDK from corresponding GPU vendor also.SETI apps news
We're not gonna fight them. We're gonna transcend them.

I have occasional terminal only access (20 - 30 hours per month) to a Ubuntu 17.10 machine running dual Tesla V100's. I'm not a developer but I can get around the terminal decently and the box gets wiped and re-imaged often so I can install/do whatever needs to be done. I'm already familiar with getting Cuda 9.2 downloaded and installed and I've run other BOINC projects on that box for testing. If I can help let me know.

I have occasional terminal only access (20 - 30 hours per month) to a Ubuntu 17.10 machine running dual Tesla V100's. I'm not a developer but I can get around the terminal decently and the box gets wiped and re-imaged often so I can install/do whatever needs to be done. I'm already familiar with getting Cuda 9.2 downloaded and installed and I've run other BOINC projects on that box for testing. If I can help let me know.

FYI - I was able to get the Cuda 9 specialized version which is crunching a WU in around 58 seconds. I believe I have installed it correctly (DL 7zip file, overwrote my projects directory) as on the results it says "SETI@home v8 Anonymous platform (NVIDIA GPU)" under application.

Dear Raistmer
I am waiting to upgrade my DELL Precision t3500 TU from an old NVIDIA QUADRO 5000 to a 1050 ti. I could sell the old graphics card but if you could use it, you can have it.
The TU ID is: 8023146 - DELL-9ZSX55J
Regards
George